Thermal face segmentation based on circular shortest path

Recently, research on thermal infrared human face analysis grows rapidly. However, due to the low contrast and limited information, human face in thermal infrared images is difficult to segment precisely. To overcome these shortcomings of thermal images, we propose an improved circular shortest path method in this paper. In our method, the proposed gradient based cost function enhances the gradient information and extracts detail of the original image. In addition, we propose a shape constraint by using ellipse derivative in the cost function. The constraint helps the contour to conform to the real human face. Moreover, the proposed certainty penalty term and straight path penalty term restrain the effect of the local minima regions and improve the robustness of our method. Our method could effectively extract the precise human face contour and thus segment the complete human face. Experimental results show that our method performs well for thermal infrared face segmentation, in both visual and quantitative ways.